IDRIS — Impact & Due Diligence Risk Intelligence Scoring
Methodology Whitepaper for Regulators and Investors
IDRIS
Impact & Due Diligence Risk Intelligence Scoring
A composite impact scoring framework for investment due diligence, covering projects from €1,500 to €50,000,000 across worldwide geographies. Compliant with EU Taxonomy, SFDR, CSRD/ESRS, TCFD and PRIIPs/MiFID II — and going further by measuring real-world outcomes on climate, gender equity, social mobility, territory, governance, pollution and innovation.
Executive Summary
IDRIS is an impact-first due diligence scoring framework designed for investment professionals, ESG compliance officers, external investors and regulators evaluating projects from €1,500 micro-investments to €50,000,000 infrastructure and private equity transactions across all geographies.
Unlike conventional ESG rating systems — which measure corporate sustainability disclosures — IDRIS measures the real-world outcomes of an investment activity against today’s critical global challenges: climate change, gender inequality, social mobility, territorial wealth distribution, pollution, corruption and democratic governance.
The framework operates on two layers:
- Regulatory compliance gate — verifies adherence to the five applicable EU frameworks (EU Taxonomy, SFDR, CSRD/ESRS, TCFD, PRIIPs/MiFID II)
- Extended impact composite score — measures transformative outcomes across eight dimensions, weighted to reflect the empirically-established hierarchy of social determinants
The central methodological departure from ESG is the Social Priority Principle: gender equity, social mobility and governance together account for 50% of the total score, on the basis that social determinants are upstream of all other outcomes. A project delivering strong climate metrics but failing on gender equity or local value creation is extractive, not transformative. IDRIS will not classify it as green.
This whitepaper is addressed to four audiences: investment analysts who use the scoring app daily; ESG and compliance officers who need to map outputs to regulatory obligations; external investors and LPs who need to understand methodology robustness; and regulators (AMF, ECB, EBA) who need to verify that the framework meets or exceeds current EU requirements.
1 The Problem with ESG
1.1 ESG Measures Disclosure, Not Outcome
The widespread adoption of ESG frameworks since 2015 has produced a paradox: the volume of sustainability disclosure has increased dramatically while the measurable real-world outcomes on climate, inequality and biodiversity have continued to deteriorate. The reason is structural. ESG frameworks — including those mandated by SFDR and CSRD — measure whether a company reports on environmental and social risks, not whether its activities produce positive outcomes for people and ecosystems.
A coal company with excellent sustainability reporting will score well on SFDR PAI disclosure. A microfinance institution in rural Senegal with no compliance department will score poorly. The signal is inverted relative to impact.
2 The IDRIS Framework
2.1 Design Principles
IDRIS was designed around five principles drawn from the impact investment literature (IMP, GIIN, Bridgespan Group, UNDP SDG Finance):
Additionality. The framework rewards investments that go beyond what would have happened anyway — projects in underserved geographies, underfinanced sectors, or with explicit inclusion mandates score higher than equivalent projects in well-served markets.
Materiality. Scores are weighted toward dimensions where the investment has measurable causal influence — a microfinance project has high gender and social materiality; a renewable energy plant has high climate and pollution materiality.
Contextualisation. Country-level data (Transparency International CPI, ND-GAIN Climate Vulnerability Index, UNDP Human Development Index) adjusts scores for operating context. A 5 MW solar plant in Nigeria represents greater additionality than the same plant in Denmark.
Explainability. Every component of every dimension score is a simple algebraic function of observable inputs. There are no black-box transformations, no embeddings, no latent variables. Any analyst or regulator can reproduce any score from first principles using the formulas in Section 3.
Regulatory coherence. The framework is designed to be a superset of regulatory requirements — every SFDR PAI indicator is represented, every EU Taxonomy objective is addressable, every TCFD category is covered. Passing the regulatory gate is a necessary but not sufficient condition for a high IDRIS score.
2.2 Architecture Overview
Gender < 30 OR Social < 30
→ Band capped at Amber
Weighted sum 0–100
Band: Red / Amber / Green / Dark Green
3 Dimension Scoring Methodology
3.4 Governance & Anti-Corruption (15%)
What it measures: The institutional quality of the operating environment, the transparency of ownership structures, and the exposure to corruption, money laundering and regulatory arbitrage.
Formula:
\[\Gamma = \frac{\text{CPI}}{100} \cdot 65 + \delta_{\text{EU}} \cdot 20 + \delta_{\text{asset}} \cdot 10\]
Where \(\delta_{\text{EU}}\) is 1 if the project is in an EU member state (EU regulatory perimeter provides enhanced investor protection, AML enforcement and beneficial ownership transparency), and \(\delta_{\text{asset}}\) is 1 if the asset class is Green Bond or Project Finance (both require structured governance frameworks).
This dimension maps directly to SFDR PAI indicators 16 (exposure to controversial weapons) and 17 (tax jurisdiction), and to CSDDD Article 3 due diligence requirements on governance of value chain partners.
3.5 Climate & Environment (18%)
Formula:
\[C = (1 - \gamma) \cdot 70 + \delta_{\text{tax}} \cdot 20 - V \cdot 15 + \sigma \cdot 5\]
Where \(\gamma\) is GHG intensity (0–1, sector default or analyst override), \(\delta_{\text{tax}}\) is 1 if the sector is EU Taxonomy-eligible, \(V\) is the ND-GAIN climate vulnerability score (0–1) for the country of operation, and \(\sigma\) is the size factor.
The vulnerability deduction reflects physical climate risk: a project operating in a highly climate-vulnerable territory faces greater risk of stranded assets and reduced long-term climate contribution. This term links directly to TCFD physical risk assessment.
3.6 Pollution & Health (10%)
Formula:
\[P = (1 - \gamma) \cdot 75 + \delta_{\text{tax}} \cdot 20\]
A simplified function of GHG intensity and taxonomy eligibility. Projects with low emissions intensity and in taxonomy-eligible sectors (which must pass DNSH on pollution prevention) receive the highest scores. Maps to EU Taxonomy Objective 3 (prevention and control of pollution).
3.7 Water & Resources (8%)
Formula:
\[W = 70 - \Delta_{\text{water}} - V \cdot 20\]
Where \(\Delta_{\text{water}}\) is 40 if GHG intensity > 0.4 (water-intensive sectors such as extractive industry and heavy manufacturing), otherwise \(\gamma \times 30\). Maps to EU Taxonomy Objective 4 and SFDR PAI 6 (water usage and recycling).
3.8 Territory & Local Wealth (8%)
Formula:
\[T = 30 + (1 - \text{HDI}) \cdot 40 + \delta_{\text{EU}} \cdot 20 + \sigma \cdot 10\]
The \((1 - \text{HDI}) \cdot 40\) term encodes a key principle: investments in lower-development territories have greater additionality potential. A €500,000 microfinance project in rural Ethiopia has greater territorial development impact than the same amount invested in a French urban SME, even if the French project is better governed. This does not reward poor governance — the governance dimension handles that separately. It rewards geographic additionality.
3.9 Innovation & Resilience (6%)
Formula:
\[I = 40 + \delta_{\text{innov}} \cdot 30 + \sigma \cdot 20 + \text{HDI} \cdot 10\]
Where \(\delta_{\text{innov}}\) is 1 for sectors classified as innovation-intensive: Renewable Energy, Digital Infrastructure, Clean Transportation, Energy Efficiency, Circular Economy, Education & Skills, Financial Inclusion, Water & Sanitation.
5 Regulatory Framework Mapping
5.1 EU Taxonomy
The IDRIS framework maps to all six EU Taxonomy environmental objectives:
| Obj. | Description | IDRIS dimensions |
|---|---|---|
| 1 | Climate change mitigation | Climate (18%), Pollution (10%) |
| 2 | Climate change adaptation | Climate (18%), Territory (8%) |
| 3 | Sustainable use of water | Water (8%) |
| 4 | Circular economy | Water (8%), Innovation (6%) |
| 5 | Pollution prevention | Pollution (10%) |
| 6 | Biodiversity | Climate (18%), Water (8%) |
Taxonomy eligibility is assessed by sector classification. Taxonomy alignment requires passing the Do No Significant Harm (DNSH) test (GHG intensity < 0.50 AND climate vulnerability < 0.70) and achieving a Substantial Contribution score > 40%.
5.2 SFDR Principal Adverse Impact Indicators
All 18 mandatory PAI indicators are represented in the IDRIS aggregate PAI score:
| PAI | Description | IDRIS mapping |
|---|---|---|
| 1 | GHG emissions intensity | Climate, Pollution dimensions |
| 2 | Carbon footprint | Climate dimension |
| 3 | GHG intensity of investee companies | Climate dimension |
| 4 | Exposure to fossil fuel sector | Sector classification |
| 5 | Non-renewable energy consumption | Climate, Innovation |
| 6 | Energy consumption intensity | Water dimension |
| 7 | Biodiversity-sensitive areas | Climate dimension |
| 8 | Water emissions | Water dimension |
| 9 | Hazardous waste | Pollution dimension |
| 10 | Violations of UNGC / OECD | Governance dimension |
| 11 | Lack of UNGC / OECD process | Governance dimension |
| 12 | Unadjusted gender pay gap | Gender dimension |
| 13 | Board gender diversity | Gender dimension |
| 14 | Exposure to controversial weapons | Governance dimension |
| 15 | GHG intensity (real estate) | Climate dimension |
| 16 | Energy performance (real estate) | Climate dimension |
| 17 | Exposure to fossil fuels (real estate) | Climate dimension |
| 18 | Exposure to energy-inefficient assets | Climate dimension |
5.3 SFDR Article Classification Logic
5.4 TCFD Climate Risk Assessment
IDRIS generates two TCFD risk flags per project:
Physical risk is derived from the ND-GAIN Climate Vulnerability Index for the country of operation. Low: vulnerability < 0.40. Medium: 0.40–0.65. High: > 0.65.
Transition risk is derived from sector classification. High-transition sectors (Extractive Industry, Manufacturing, Food & Nutrition, Private Equity diversified) face significant regulatory and market disruption risk under 1.5°C–2°C pathways. Low- transition sectors (Renewable Energy, Energy Efficiency, Clean Transportation, Circular Economy, Biodiversity) are net beneficiaries of the transition.
5.5 CSRD / ESRS Double Materiality
Following the 2025 Omnibus revision, CSRD applies to companies with > 1,000 employees and > €450M turnover. IDRIS applies a proxy rule: projects with investment > €5M in EU jurisdictions outside financial inclusion sectors are flagged as likely in-scope for CSRD reporting by the investee company.
Double materiality flags are generated for impact materiality (does the activity have significant environmental or social impacts?) and financial materiality (are sustainability risks material to the financial performance of the investment?).
5.6 PRIIPs / MiFID II Suitability
IDRIS generates a MiFID II suitability score (0–10) for each project, combining the IDRIS composite score, SFDR article classification and TCFD risk flags. This feeds directly into investor preference matching under MiFID II Article 9(1)(a) sustainability preference assessment, enabling portfolio-level suitability reporting.
6 Score Bands and Decision Framework
| Band | Score range | Recommended SFDR | Decision guidance |
|---|---|---|---|
| Dark Green | 75 – 100 | Article 9 | Flagship impact investment. Full Taxonomy alignment typically achieved. Suitable for Article 9 product eligibility. |
| Green | 58 – 74 | Article 8 | Strong impact profile. Promotes E/S characteristics. Article 8 product eligible with documented E/S binding elements. |
| Amber | 40 – 57 | Article 6 or 8 | Mixed profile. Review dimension weaknesses. Social veto may be active. Additional due diligence recommended before classification. |
| Red | 0 – 39 | Article 6 | Significant adverse impacts identified. Not suitable for impact mandate. Investment should be declined or substantially restructured. |
7 Country and Sector Reference Data
7.1 Country Context Indices
Country calibration data is sourced from three publicly available, annually-updated indices:
- Transparency International Corruption Perceptions Index (CPI) — used in governance and gender dimension scoring. Scores range 0–100 (0=highly corrupt, 100=very clean). 2023 data.
- Notre Dame Global Adaptation Initiative (ND-GAIN) Climate Vulnerability Index — used in climate and water dimension scoring and TCFD physical risk classification. Scores range 0–1 (0=low vulnerability, 1=high vulnerability). 2022 data.
- UNDP Human Development Index (HDI) — used in social mobility, gender, territory and innovation dimension scoring. Scores range 0–1 (0=low development, 1=very high development). 2023 data.
The framework covers 50 countries spanning all major investment geographies. For unlisted countries, a conservative default (CPI=45, Vuln=0.50, HDI=0.70) is applied.
7.2 Sector Taxonomy Eligibility
| Sector | Taxonomy eligible | GHG intensity | Social tier |
|---|---|---|---|
| Renewable Energy | Yes | Very low (0.05) | Medium |
| Energy Efficiency | Yes | Low (0.10) | Medium |
| Water & Sanitation | Yes | Very low (0.08) | High |
| Clean Transportation | Yes | Low (0.15) | Medium |
| Green Building / Real Estate | Yes | Low (0.20) | Medium |
| Circular Economy | Yes | Low (0.18) | Medium |
| Biodiversity / Nature | Yes | Very low (0.05) | Medium |
| Sustainable Agriculture | Yes | Medium (0.35) | High |
| Social Infrastructure | Yes | Low (0.10) | High |
| Healthcare | No | Low (0.22) | High |
| Education & Skills | No | Low (0.12) | High |
| Financial Inclusion / Microfinance | No | Very low (0.10–0.15) | High |
| Affordable Housing | No | Low (0.28) | High |
| Digital Infrastructure | No | Medium (0.25) | Low |
| SME Finance | No | Medium (0.30) | Medium |
| Food & Nutrition | No | Medium-high (0.42) | Medium |
| Manufacturing (conventional) | No | High (0.65) | Low |
| Extractive Industry | No | Very high (0.85) | Low |
8 Validation and Benchmarking
8.1 Synthetic Dataset
The IDRIS framework was developed and validated against a synthetic benchmark dataset of 2,000 investment projects generated using the generate_data.py module. The dataset covers all 50 countries, all 20 sectors, all 6 asset classes, and a log-uniform distribution of investment sizes from €1,500 to €50,000,000.
Dataset statistics (2,000 projects):
| Metric | Value |
|---|---|
| IDRIS score range | 23.3 – 84.0 |
| Mean IDRIS score | 58.5 |
| Article 9 classification | 9.7% |
| Article 8 classification | 70.4% |
| Article 6 classification | 19.9% |
| Taxonomy aligned | 40.1% |
| Social veto triggered | 1.1% |
| Dark Green band | 5.4% |
| Green band | 50.2% |
| Amber band | 37.6% |
| Red band | 6.9% |
8.2 Score Coherence Checks
Three properties of the scoring system were validated against prior expectations:
Geographic ordering. Nordic EU member states (Denmark, Sweden, Norway) consistently score highest; sub-Saharan Africa and South Asia score lowest on average. This reflects the CPI, HDI and climate vulnerability differentials across regions. The scoring correctly does not penalise low-HDI countries for having lower development scores — the territory dimension includes an additionality term that rewards investment in underserved geographies.
Sector ordering. Renewable Energy, Education and Microfinance score highest; Extractive Industry and conventional Manufacturing score lowest. The ordering is consistent across geographies — a renewable energy project in Nigeria scores higher than an extractive project in Denmark.
Social veto coherence. The 22 veto-triggered projects in the dataset are exclusively in high-corruption, low-development geographies with extractive or low-social-factor sectors. No EU-member-state project triggers the veto. No social-sector project (healthcare, education, microfinance) triggers the veto in any geography.
9 Limitations and Future Development
9.1 Current Limitations
Sector granularity. The current implementation uses 20 sector categories. Real-world projects often span multiple sectors or represent niche activities not well-captured by the taxonomy. Future versions will support multi-sector blending with user-defined sector weights.
Analyst data dependency. The framework produces strongest results when analysts provide project-specific data (actual GHG intensity, measured gender pay gap, governance audit results). In the absence of such data, sector and country defaults are applied — these are calibrated to be conservative but cannot substitute for field due diligence.
Dynamic index updates. CPI, HDI and ND-GAIN data are updated annually. The framework requires an annual recalibration of country reference data to remain current.
Social veto threshold calibration. The 30/100 threshold for the Social Veto Rule was set by expert judgment and validated against the synthetic dataset. A formal empirical calibration against real investment outcomes data would strengthen its defensibility before regulators.
9.2 Roadmap
- v1.1: Multi-sector blending, SFDR annex template auto-generation
- v1.2: Integration with Bloomberg ESG, MSCI ESG and Sustainalytics data APIs
- v1.3: Portfolio-level aggregation and fund-level SFDR entity reporting
- v2.0: Machine learning calibration layer trained on verified impact outcomes data from GIIN, IFC and development finance institutions
10 References
- European Commission (2020). Regulation (EU) 2020/852 on the establishment of a framework to facilitate sustainable investment (EU Taxonomy Regulation).
- European Commission (2019). Regulation (EU) 2019/2088 on sustainability-related disclosures in the financial services sector (SFDR).
- European Commission (2022). Directive (EU) 2022/2464 on Corporate Sustainability Reporting (CSRD).
- European Commission (2022). Directive (EU) 2022/2523 on Corporate Sustainability Due Diligence (CSDDD).
- TCFD (2017). Recommendations of the Task Force on Climate-related Financial Disclosures. Financial Stability Board.
- Transparency International (2023). Corruption Perceptions Index 2023.
- UNDP (2023). Human Development Report 2023/24. United Nations Development Programme.
- University of Notre Dame (2022). ND-GAIN Country Index. Notre Dame Global Adaptation Initiative.
- GIIN (2020). IRIS+ System for Impact Measurement and Management. Global Impact Investing Network.
- IMP (2019). A Guide to Classifying the Impact of an Investment. Impact Management Project.
- World Bank (2023). Women, Business and the Law 2023.
- ILO (2022). World Employment and Social Outlook 2022. International Labour Organization.
- Allen, T. et al. (2016). Social Mobility and Its Drivers. OECD Publishing.
- Bridgespan Group (2021). The State of Impact Measurement.
3.3 Social Mobility (15%)
What it measures: The degree to which the investment creates durable economic opportunity for local communities — employment quality, skills transfer, living wage access, and the share of economic value retained in the territory.
Formula:
\[S = s_f \cdot 50 + \text{HDI} \cdot 25 + \sigma \cdot 15 + b - (1 - \text{HDI})(1 - s_f) \cdot 25\]
Where \(s_f\) is the sector social factor (0.82 for high-social sectors, 0.38 for extractive, 0.60 otherwise), \(\sigma\) is the investment size factor (log-normalised 0–1), and \(b\) is a sector bonus (+15 for Healthcare, Education, Microfinance, Financial Inclusion, Social Infrastructure, Affordable Housing, Water & Sanitation).
The structural deprivation penalty term \((1 - \text{HDI})(1 - s_f) \cdot 25\) ensures that an extractive industry project in a low-development country cannot achieve a high social mobility score — even at large scale. It is specifically designed to prevent large-ticket infrastructure projects in low-HDI countries from scoring well through scale alone without genuine local value creation.
Social Veto Rule: If Social score < 30, the project band is capped at Amber.